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What Tech Carriers, Forwarders, and Shippers Think Will Shape 2026 Freight Procurement

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What Tech Carriers, Forwarders, and Shippers Think Will Shape 2026 Freight Procurement

October 29, 2025

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The recent FreighTech 2025 conference once again brought together a mix of carriers, forwarders, BCOs, academics, and tech providers to hear the latest and share insights around, logistics technology and how it can benefit the freight industry.

Key Tech Trends for Global Freight in 2026

From AI to ocean freight innovation and tendering strategies for 2026, here are some of the key takeaways from this year’s event.

AI is already having an impact, especially in data processing and customer support, with expectations to manage 20% of human tasks within five years – though most organizations aren’t fully AI-ready yet.

Data quality challenges and few standards remain an obstacle for tech implementation, including for AI projects.

Ocean freight digitalization is progressing, with improved carrier APIs expected to trigger a digital transformation similar to what’s occurred in air cargo.

Strategic approaches to tendering are maturing, as technology tools for pricing visibility and rate discovery are helping companies move away from underutilized contracts on low-volume lanes toward a more balanced contract/spot strategy – as MIT research presented at the conference recommends.

Index-linked freight contracts are gaining traction as these flexible agreements are proving beneficial for all parties,often offering better costs, revenue, and reliability than traditional fixed contracts.

AI for Global Freight: Potential, Reality and Best Practices

Key Takeaways:

AI is already being used aggressively, mostly with data processing, automation and front-line customer support.

It’s still just getting started; leaders have high expectations to handle more tasks in coming years with human roles mostly evolving, rather than being eliminated, as a result.

Many are convinced that AI will have a net negative impact on sector employment.

Leaders don’t feel completely ready yet

AI was, as expected, a hot topic this year and top of mind for most in attendance. But discussion focussed on separating current practical AI applications for logistics from the hype, setting realistic horizons, and sharing lessons learned to date.

An audience poll showed expectations that within the next few years AI will handle a meaningful share of current logistics tasks currently done by humans – over half of leaders believe that at least 20% of current roles could be handled by AI in the next five years.

But there was also consensus that, along with some admitted reduction in headcount, human roles will evolve along with AI advances. Logistics professionals will leverage AI to enable teams to do more, and add more value for customers in new ways – just as many logistics tech introductions to date have enhanced instead of eliminated human roles.

Freight is complicated, however, and speakers agreed that AI can’t do it all, and not right away. At the same time, AI is already being applied in multiple ways across the freight landscape, especially for mundane and repetitive tasks. Some examples include using AI to:

Detect data anomalies or process unstructured data

Create content

Enable automation flow between systems

Power agents (and even voicebots) that handle routine customer inquiries or internal processes.

They still aren’t ready though.

That being said, only about a third in attendance consider their organizations AI-ready.

As such, best practices for AI investment, development, and introductions for logistics from those already at the forefront focussed on the following main recommendations:

Problem Mapping: Identify high-impact, high-frequency problems where AI is already likely to add value

Start Small: Begin with clear use cases and expand based on success

Focus: Build AI capabilities in areas where your company has deep domain expertise, and buy solutions for everything else

Experiment and share: Make AI tools available to teams for experimentation and facilitate knowledge sharing.

Data Quality – the Persistent Roadblock

Key Takeaways:

Lack of standards and inconsistent data remains a frustrating roadblock, including for AI

Focus on data that does work; scale from there

But even alongside the excitement surrounding AI, there was a familiar refrain that poor data quality – often from data received from partners in the supply chain, and attributable to the ongoing lack of freight data standards – continues to frustrate some logistics tech aspirations, including AI projects.

“Discovering something you can’t do right now is also important, and opens new opportunities to do that thing, and maybe more, in the future. In this case it showed the value of investing in quality data.” – Robert Khachatryan, CEO FreightRight

Robert Khachatryan of FreightRight shared a case study of the forwarder’s attempt to build an AI-driven predictive pricing system pilot with data scientists from USC. But the project had to be scrapped when they realized that much of their necessary historical freight rate data – where the inputs are complex and varied – was not clean enough to enable AI to succeed in the task.

The lesson learned was that investing in data quality now will enable successful tech, including AI, in the future.

“On the carrier side, we’ve established a shared understanding of what information we can easily exchange right now, and so we focus on that available data for digital solutions, to improve our efficiency and the customer experience.” – Helge Neumann-Lezius, Head of FCL, Hellmann

Helge Neumann-Lezius from Hellmann offered Hellman’s similar pragmatic approach to tech investment and roll outs: focus on building around the quality data you have now, while taking steps to improve data quality in other areas.

Ocean Innovation: Nearing a Digital Tipping Point

Key Takeaways:

Ocean liners are beginning to improve access to APIs

This will likely help fuel the same surge in connectivity that airline APIs have offered.

An example of this strategy is Hellman’s focus on more real-time data exchange with ocean carriers, leveraging improved API connections with carriers to enable real-time rate and tracking data.

So while ocean freight’s digital adoption has lagged air cargo’s – where API-enabled dynamic rates, market intelligence, and eBookings, including through third party platforms, are becoming more and more prevalent – several speakers suggested that ocean is approaching its tipping point.

The logistics supply chain is often only as digitalized as its least digital partner, so as ocean carrier connectivity improves the near term is likely to see a surge in digital ocean freight, including real-time rates, online bookings and TMS integrations.

Tendering in 2026: Finding the Right Balance

Key Takeaways:

Long term contracts are assumed to be the default solution for tendering but can be unreliable or underutilized

Spot freight – used strategically – can reduce costs and save time

Index-linked contracts and even hedging are gathering momentum after many years of discussion.

Looking ahead to 2026, several discussions on ocean freight tendering for the coming year revealed interesting recommendations for striking a contract vs. spot balance, explored the growing prevalence of index-linked contracts, and shared how tech is playing a larger role here as well.

Dr. Angi Acocella of MIT’s Center for Transportation and Logistics shared her recent research showing that shippers in both FTL and ocean rely on long term contracts for the big majority of their volumes, using spot to manage uncertainty – mostly for unexpected volumes, one-off shipments or lanes, or when contracted carriers are unavailable.

But the research also showed an 80/20 split: 80% of shipper volumes go on 20% of the contracted lanes, leaving many contracts for lower-volume lanes underutilized. Unused contracts not only cost shippers in the form of wasted time and resources on negotiations, but also often entail higher rates for shipments moved on these lanes – often at levels above spot costs for those shipments – and slightly higher contract rates on high volume lanes as well.

As such, she recommends examining lane volumes, contract rates and spot usage and costs from the previous year. Shippers are advised to focus contracts on the higher volume lanes, and rely more on spot for the long tail.

Research also shows the growing place for index-linked contracts in freight, and evidence that index-linked contracts benefit both carriers and shippers in the form of lower costs, increased revenue and better volume reliability than non-linked contracts or the spot market.

Multiple speakers noted the importance of trust for index-linked pilots – trust between the partners, in the rate data selected as the basis, and in the contract mechanism. As these grow, index-linked contract adoption is expected to grow as well.

Finally, speakers touched on the increased importance of technology to procurement. Tools that improve pricing/volume visibility, rate discovery, and the speed and efficiency of communication between carriers/LSPs/shippers already contribute to the ability to make better and strategic tendering decisions. Tech-enabled improvements in these areas are helping shippers and LSPs make the procurement process – for both tenders and spot shipments – less costly, faster, more efficient, and more reliable.
If you enjoyed this, you may also enjoy our recent virtual summit, which included discussions of digital freight transformation, spot/tender balances, and more. See it here.

Judah Levine

Head of Research, Freightos Group

Judah is an experienced market research manager, using data-driven analytics to deliver market-based insights. Judah produces the Freightos Group’s FBX Weekly Freight Update and other research on what’s happening in the industry from shipper behaviors to the latest in logistics technology and digitization.

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Join us for Tomorrow’s Webinar: Building a Sustainable Supply Chain: Turning Commitments into Competitive Advantage

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Join Us For Tomorrow’s Webinar: Building A Sustainable Supply Chain: Turning Commitments Into Competitive Advantage

Sustainability has moved beyond corporate responsibility. Today, it’s a core element of supply chain performance and brand value. Organizations across every sector are rethinking how materials are sourced, products are moved, and data is managed to reduce emissions, improve efficiency, and strengthen resilience.

Join us for an in-depth Logistics Viewpoints webinar on Sustainability in the Supply Chain, where industry leaders will share how they are embedding environmental and social responsibility into the fabric of their operations. This session will explore practical steps for achieving measurable progress — not just pledges — in areas such as supplier engagement, energy management, and circular logistics.

Key topics include:

Proven frameworks for integrating sustainability into procurement and manufacturing
Tools and metrics for tracking emissions and improving data visibility
How transparency and collaboration can reduce risk and enhance competitiveness
Lessons learned from companies leading the charge toward carbon-smart logistics

Our expert panel will focus on real-world case studies and actionable takeaways, giving attendees insights they can immediately apply to strengthen their sustainability programs.

Whether your organization is just beginning its journey or refining an established strategy, this webinar offers a roadmap to align sustainability goals with measurable business outcomes.

Register now to join us live and learn how forward-thinking companies are transforming sustainability from a compliance obligation into a competitive advantage.

The post Join us for Tomorrow’s Webinar: Building a Sustainable Supply Chain: Turning Commitments into Competitive Advantage appeared first on Logistics Viewpoints.

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Stellantis: $13 Billion, 5,000 Jobs, and a New U.S. Manufacturing Strategy, Reshaping the North American Supply Chain

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Stellantis: $13 Billion, 5,000 Jobs, And A New U.s. Manufacturing Strategy, Reshaping The North American Supply Chain

AUBURN HILLS, MI. Stellantis announced plans to invest $13 billion over the next four years to expand its U.S. manufacturing footprint. The initiative will add more than 5,000 jobs across Illinois, Ohio, Michigan, and Indiana and increase U.S. vehicle production by about 50 percent.

The investment will fund five new vehicle programs, 19 product refreshes, and a new four-cylinder engine program. It is the company’s largest single U.S. investment and signals a long-term commitment to both internal combustion and electrified vehicle platforms.

“This investment in the U.S. will drive our growth, strengthen our manufacturing footprint, and bring more American jobs to the states we call home,” said Antonio Filosa, Stellantis CEO and North America COO. “As we begin our next 100 years, we are putting the customer at the center of our strategy, expanding our vehicle offerings, and giving them the freedom to choose the products they want and love.”

“Accelerating growth in the U.S. has been a top priority since my first day,” Filosa added. “Success in America is not just good for Stellantis in the U.S. It makes us stronger everywhere.”

State-by-State Overview

Illinois: Belvidere Plant Reopening
Stellantis will invest $600 million to reopen the Belvidere Assembly Plant for production of two Jeep models, the Cherokee and Compass, beginning in 2027. The project is expected to create 3,300 jobs.

Ohio: New Midsize Truck Production
About $400 million will fund production of an all-new midsize truck at the Toledo Assembly Complex, joining the Jeep Wrangler and Gladiator lines. The move will add about 900 positions when production begins in 2028. Additional upgrades are planned across Toledo operations to support ongoing Jeep production.

Michigan: Large SUV and Dodge Durango Successor
At the Warren Truck Assembly Plant, Stellantis will invest $100 million to produce a new large SUV available in both range-extended EV and combustion formats. The launch, expected in 2028, will add 900 jobs. Another $130 million will prepare the Detroit Assembly Complex, Jefferson, for the next-generation Dodge Durango, slated for production in 2029.

Indiana: New Engine Program
In Kokomo, Stellantis will invest more than $100 million to build the new GMET4 EVO four-cylinder engine. Production is set to begin in 2026 and will add about 100 jobs.

Supply Chain and Logistics Considerations

The Stellantis plan reflects a larger trend toward regionalized manufacturing and shorter supply chains. By expanding production in the Midwest, Stellantis is reducing exposure to overseas logistics risks and shipping delays that have challenged the industry in recent years.

Reopening Belvidere and expanding operations in Toledo and Kokomo will strengthen domestic supplier ecosystems for components such as engines, drivetrains, and electronics. Adding dual powertrain lines, both EV and ICE, will require parallel material streams and more sophisticated synchronization between inbound logistics, supplier planning, and workforce scheduling.

At the same time, expansion across multiple states increases the complexity of coordination and sourcing. Tier-1 suppliers will need to adjust production capacity, labor allocation, and transportation networks to align with Stellantis’ new programs. Global lead times for critical components such as semiconductors, battery modules, and sensors remain unpredictable, requiring early-stage visibility and contingency planning.

For the broader supply chain, the challenge lies in maintaining steady component availability while scaling new vehicle lines and managing cost pressures tied to both traditional and electrified platforms.

Outlook

Stellantis operates 34 U.S. facilities across 14 states and employs more than 48,000 people. This new investment deepens that footprint and aligns with an operational goal of building greater resilience and control within the domestic production network.

For supply chain leaders, Stellantis’ move highlights the continued shift toward regional production, flexible sourcing strategies, and closer collaboration between OEMs and their supplier networks. The focus now is not just on capacity but on stability, adaptability, and execution across interconnected plants and partner

The post Stellantis: $13 Billion, 5,000 Jobs, and a New U.S. Manufacturing Strategy, Reshaping the North American Supply Chain appeared first on Logistics Viewpoints.

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OpenAI and AWS Forge $38B Alliance, Microsoft Exclusivity Ends, New Multi-Cloud AI Compute Era Begins

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Openai And Aws Forge $38b Alliance, Microsoft Exclusivity Ends, New Multi Cloud Ai Compute Era Begins

OpenAI has entered into a multi-year, $38 billion agreement with Amazon Web Services, formally ending its exclusive reliance on Microsoft Azure for cloud infrastructure. The deal, announced today, represents a fundamental realignment in the cloud compute ecosystem supporting advanced AI workloads.

Under the agreement, OpenAI will immediately begin running large-scale training and inference operations on AWS, gaining access to hundreds of thousands of NVIDIA GPUs hosted on Amazon EC2 UltraServers, along with the ability to scale across tens of millions of CPUs over the next several years.

“Scaling frontier AI requires massive, reliable compute,” said Sam Altman, OpenAI’s CEO. “Our partnership with AWS strengthens the broad compute ecosystem that will power this next era.”

A Structural Shift Toward Multi-Cloud AI

This marks the first formal infrastructure partnership between OpenAI and AWS. Since 2019, Microsoft has provided the primary compute backbone for OpenAI, anchored by a $13 billion investment and multi-year Azure commitment. That exclusivity expired earlier this year, opening the door to a multi-provider model.

AWS now becomes OpenAI’s largest secondary partner, joining smaller agreements already in place with Google Cloud and Oracle, and positioning itself as a co-equal pillar in OpenAI’s global compute strategy.

“AWS brings both scale and maturity to AI infrastructure,” noted Matt Garman, AWS CEO. “This agreement demonstrates why AWS is uniquely positioned to support OpenAI’s demanding AI workloads.”

Infrastructure Scope and Deployment

The deployment will include clusters of NVIDIA GB200 and GB300 GPUs linked through UltraServer nodes engineered for low-latency, high-bandwidth interconnects. The architecture supports both model training and large-scale inference, applications such as ChatGPT, Codex, and next-generation multimodal systems.

AWS has already begun allocating capacity, with full deployment expected by late 2026. The framework also includes options for expansion into 2027 and beyond, giving OpenAI flexibility as model complexity and usage continue to grow.

Continued Microsoft Collaboration

Despite the AWS deal, OpenAI maintains its strategic and financial relationship with Microsoft, including a separate $250 billion incremental commitment to Azure. The move reflects a deliberate multi-cloud posture, a strategy increasingly favored by large-scale AI developers seeking to balance cost, access to specialized chips, and platform resiliency.

Implications for Supply Chain and Infrastructure Leaders

This announcement underscores several macro-trends relevant to logistics and industrial technology executives:

AI Infrastructure Is Becoming a Supply Chain of Its Own
Cloud capacity, GPUs, and networking fabric are now constrained global commodities. Long-term compute contracts mirror procurement models traditionally seen in manufacturing or energy, locking in scarce resources ahead of demand.
Multi-Cloud Neutrality Reduces Vendor Lock-In
The shift toward multiple cloud providers parallels how diversified sourcing reduces single-supplier risk. Expect enterprise buyers to apply similar logic when procuring AI infrastructure and software services.
Operational AI at Scale Requires Cross-Vendor Interoperability
As companies like OpenAI distribute workloads across ecosystems, interoperability standards, ranging from APIs to data-plane orchestration, will become critical for continuity, performance, and governance.
CapEx Discipline Returns to the Forefront
With multi-year AI compute deals now exceeding $1.4 trillion in aggregate commitments across the sector, CFOs and CIOs are under pressure to evaluate utilization efficiency and long-term ROI of their AI infrastructure spend.

Broader Market Context

AWS’s win follows similar capacity expansions with Anthropic and Stability AI, but this partnership represents its highest-profile AI infrastructure engagement to date. It also signals that OpenAI intends to maintain independence in its technical roadmap, balancing strategic investors with diversified operational suppliers.

The timing is notable: OpenAI recently restructured its governance model to simplify corporate oversight, a move analysts interpret as preparation for a potential IPO that could value the company near $1 trillion.

AWS stock rose approximately 5 percent following the announcement, reflecting investor confidence in the long-term demand for AI-class compute.

Outlook

For the logistics and manufacturing sectors, the implications extend beyond software. The same GPU-based data centers that train language models are also powering digital twins, simulation models, and optimization engines increasingly embedded in supply chain planning.

As hyperscalers compete for AI workloads, enterprises should expect faster innovation in distributed computing, lower latency connectivity, and new pay-as-you-go models designed for AI-intensive industrial applications.

Summary

The $38 billion OpenAI–AWS partnership marks a decisive end to Microsoft’s exclusivity and a broader normalization of multi-cloud AI ecosystems.
For technology and supply-chain leaders, it serves as a reminder: compute itself has become a strategic resource, one that must now be sourced, diversified, and managed with the same rigor once reserved for physical inventory.

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